Publication Date:
2019-07-13
Description:
Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.
Keywords:
Meteorology and Climatology; Earth Resources and Remote Sensing
Type:
M14-3235
,
Canadian Symposium on Remote Sensing; Jul 13, 2014 - Jul 18, 2014; Quebec City; Canada|International Geoscience and Remote Sensing Symposium (IGARSS 2014); Jul 13, 2014 - Jul 18, 2014; Quebec City; Canada
Format:
application/pdf
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